def test__mapping_repr(display_max_rows, n_vars, n_attr) -> None:
long_name = "long_name"
a = defchararray.add(long_name, np.arange(0, n_vars).astype(str))
b = defchararray.add("attr_", np.arange(0, n_attr).astype(str))
c = defchararray.add("coord", np.arange(0, n_vars).astype(str))
attrs = {k: 2 for k in b}
coords = {_c: np.array([0, 1]) for _c in c}
data_vars = dict()
for (v, _c) in zip(a, coords.items()):
data_vars[v] = xr.DataArray(
name=v,
data=np.array([3, 4]),
dims=[_c[0]],
coords=dict([_c]),
)
ds = xr.Dataset(data_vars)
ds.attrs = attrs
with xr.set_options(display_max_rows=display_max_rows):
# Parse the data_vars print and show only data_vars rows:
summary = formatting.dataset_repr(ds).split("\n")
summary = [v for v in summary if long_name in v]
# The length should be less than or equal to display_max_rows:
len_summary = len(summary)
data_vars_print_size = min(display_max_rows, len_summary)
assert len_summary == data_vars_print_size
summary = formatting.data_vars_repr(ds.data_vars).split("\n")
summary = [v for v in summary if long_name in v]
# The length should be equal to the number of data variables
len_summary = len(summary)
assert len_summary == n_vars
summary = formatting.coords_repr(ds.coords).split("\n")
summary = [v for v in summary if "coord" in v]
# The length should be equal to the number of data variables
len_summary = len(summary)
assert len_summary == n_vars
with xr.set_options(
display_max_rows=display_max_rows,
display_expand_coords=False,
display_expand_data_vars=False,
display_expand_attrs=False,
):
actual = formatting.dataset_repr(ds)
col_width = formatting._calculate_col_width(ds.variables)
dims_start = formatting.pretty_print("Dimensions:", col_width)
dims_values = formatting.dim_summary_limited(ds,
col_width=col_width + 1,
max_rows=display_max_rows)
expected = f"""\
<xarray.Dataset>
{dims_start}({dims_values})
Coordinates: ({n_vars})
Data variables: ({n_vars})
Attributes: ({n_attr})"""
expected = dedent(expected)
assert actual == expected
def test__mapping_repr(display_max_rows, n_vars, n_attr):
long_name = "long_name"
a = np.core.defchararray.add(long_name, np.arange(0, n_vars).astype(str))
b = np.core.defchararray.add("attr_", np.arange(0, n_attr).astype(str))
attrs = {k: 2 for k in b}
coords = dict(time=np.array([0, 1]))
data_vars = dict()
for v in a:
data_vars[v] = xr.DataArray(
name=v,
data=np.array([3, 4]),
dims=["time"],
coords=coords,
)
ds = xr.Dataset(data_vars)
ds.attrs = attrs
with xr.set_options(display_max_rows=display_max_rows):
# Parse the data_vars print and show only data_vars rows:
summary = formatting.data_vars_repr(ds.data_vars).split("\n")
summary = [v for v in summary if long_name in v]
# The length should be less than or equal to display_max_rows:
len_summary = len(summary)
data_vars_print_size = min(display_max_rows, len_summary)
assert len_summary == data_vars_print_size
def test__mapping_repr(display_max_rows, n_vars, n_attr):
long_name = "long_name"
a = np.core.defchararray.add(long_name, np.arange(0, n_vars).astype(str))
b = np.core.defchararray.add("attr_", np.arange(0, n_attr).astype(str))
attrs = {k: 2 for k in b}
coords = dict(time=np.array([0, 1]))
data_vars = dict()
for v in a:
data_vars[v] = xr.DataArray(
name=v,
data=np.array([3, 4]),
dims=["time"],
coords=coords,
)
ds = xr.Dataset(data_vars)
ds.attrs = attrs
with xr.set_options(display_max_rows=display_max_rows):
# Parse the data_vars print and show only data_vars rows:
summary = formatting.data_vars_repr(ds.data_vars).split("\n")
summary = [v for v in summary if long_name in v]
# The length should be less than or equal to display_max_rows:
len_summary = len(summary)
data_vars_print_size = min(display_max_rows, len_summary)
assert len_summary == data_vars_print_size
with xr.set_options(
display_expand_coords=False,
display_expand_data_vars=False,
display_expand_attrs=False,
):
actual = formatting.dataset_repr(ds)
expected = dedent(
f"""\
<xarray.Dataset>
Dimensions: (time: 2)
Coordinates: (1)
Data variables: ({n_vars})
Attributes: ({n_attr})"""
)
assert actual == expected